Manager, Revenue Analytics & Planning
New
Based in United StatesFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 6–10 years
- Required Skills
- Artificial IntelligenceBusiness IntelligenceData AnalysisSalesforceMicrosoft Excel
Requirements
- 6–10 years of experience in Revenue Operations, FP&A, analytics, business intelligence, or related roles.
- Previous experience managing teams or operating as a player-coach within an analytics or operations function.
- Strong expertise in revenue forecasting, financial modeling, and performance analysis.
- Proven ability to support executive decision-making through clear reporting and strategic recommendations.
- Advanced Excel and business intelligence skills, with experience building dashboards and analytical models.
- Hands-on experience with Salesforce and revenue intelligence platforms such as Clari for pipeline reporting and forecasting.
- Experience with quota planning, territory planning, capacity modeling, and sales performance measurement.
- Familiarity with AI or machine learning applications for forecasting, analytics automation, and operational efficiency.
- Strong business judgment with the ability to translate complex data into actionable insights.
- Excellent communication, collaboration, and stakeholder management skills in fast-paced environments.
Responsibilities
- Manage and mentor revenue analytics team members, starting with oversight of post-sales analytics and scaling the function as business needs evolve.
- Own revenue forecasting methodologies and improve forecast accuracy across new business, renewals, and expansion opportunities.
- Lead quarterly and annual planning processes, including capacity modeling, headcount planning, territory strategy, and quota allocation.
- Build and maintain reporting frameworks that measure pipeline health, conversion rates, sales effectiveness, customer retention, and revenue performance.
- Deliver executive and leadership-level reporting, translating complex data into clear insights and recommended actions.
- Identify pipeline gaps, forecast risks, and performance trends early, providing proactive recommendations to improve outcomes.
- Develop and maintain pre-sales analytics processes, including pipeline coverage, progression, aging analysis, and forecast support.
- Ensure reporting accuracy and consistency across dashboards, data sources, and operational workflows.
- Apply AI-driven approaches to improve forecasting models, automate insights generation, and identify revenue risks more efficiently.
- Partner closely with Revenue Operations, Sales, Finance, and leadership teams to align business goals with data-driven strategies.
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